Triple
T14966398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lunar Reconnaissance Orbiter |
E373198
|
entity |
| Predicate | instrument |
P792
|
FINISHED |
| Object |
LOLA
LOLA is a laser altimeter instrument aboard NASA's Lunar Reconnaissance Orbiter used to precisely map the Moon's topography.
|
E1130730
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: LOLA | Statement: [Lunar Reconnaissance Orbiter, instrument, LOLA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LOLA Context triple: [Lunar Reconnaissance Orbiter, instrument, LOLA]
-
A.
LOLA
LOLA is the commonly used abbreviation for "Law & Order: LA," a short-lived spin-off of the long-running "Law & Order" television franchise set in Los Angeles.
-
B.
Lola
Lola is a 1981 West German drama film directed by Rainer Werner Fassbinder, in which Armin Mueller-Stahl plays a prominent role in a story set in postwar Germany.
-
C.
Lola
Lola is a 1961 French New Wave film directed by Jacques Demy, featuring Corinne Marchand in the title role as a cabaret singer in the port city of Nantes.
-
D.
Lola
Lola is a lethal, acrobatic henchwoman and primary antagonist in the action film "Transporter 2," known for her distinctive red attire and high-impact fight scenes.
-
E.
Lola
Lola is the charismatic drag queen and performer who serves as the central catalyst for change in the musical and film "Kinky Boots."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: LOLA Triple: [Lunar Reconnaissance Orbiter, instrument, LOLA]
Generated description
LOLA is a laser altimeter instrument aboard NASA's Lunar Reconnaissance Orbiter used to precisely map the Moon's topography.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LOLA Target entity description: LOLA is a laser altimeter instrument aboard NASA's Lunar Reconnaissance Orbiter used to precisely map the Moon's topography.
-
A.
LOLA
LOLA is the commonly used abbreviation for "Law & Order: LA," a short-lived spin-off of the long-running "Law & Order" television franchise set in Los Angeles.
-
B.
Lola
Lola is a 1981 West German drama film directed by Rainer Werner Fassbinder, in which Armin Mueller-Stahl plays a prominent role in a story set in postwar Germany.
-
C.
Lola
Lola is a 1961 French New Wave film directed by Jacques Demy, featuring Corinne Marchand in the title role as a cabaret singer in the port city of Nantes.
-
D.
Lola
Lola is the charismatic drag queen and performer who serves as the central catalyst for change in the musical and film "Kinky Boots."
-
E.
Lola
Lola is a lethal, acrobatic henchwoman and primary antagonist in the action film "Transporter 2," known for her distinctive red attire and high-impact fight scenes.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e2fdcc8190bffe603db3388736 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8be122688190b20fe4450786158a |
completed | May 9, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69fe9045dd208190a51e6648c4275ff4 |
completed | May 9, 2026, 1:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe90ec50e081909ab267fee2b069bc |
completed | May 9, 2026, 1:42 a.m. |
Created at: April 10, 2026, 2:47 a.m.