Triple
T5743515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotten Tomatoes |
E126670
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
RT
RT is the commonly used abbreviation for Rotten Tomatoes, a popular website that aggregates film and television reviews and ratings.
|
E545997
|
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: RT | Statement: [Rotten Tomatoes, hasAbbreviation, RT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RT Context triple: [Rotten Tomatoes, hasAbbreviation, RT]
-
A.
RT
RT is a Russian state-funded international television network and online media outlet known for its global news coverage and often controversial, Kremlin-aligned perspectives on major events.
-
B.
TR
TR is the postcode area covering Truro and much of Cornwall in southwest England.
-
C.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
-
D.
TR
TR is the common abbreviation for the Textus Receptus, a historically influential printed Greek New Testament text that underlies many early Protestant Bible translations.
-
E.
RL
RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
- 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: RT Triple: [Rotten Tomatoes, hasAbbreviation, RT]
Generated description
RT is the commonly used abbreviation for Rotten Tomatoes, a popular website that aggregates film and television reviews and ratings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RT Target entity description: RT is the commonly used abbreviation for Rotten Tomatoes, a popular website that aggregates film and television reviews and ratings.
-
A.
RT
RT is a Russian state-funded international television network and online media outlet known for its global news coverage and often controversial, Kremlin-aligned perspectives on major events.
-
B.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
-
C.
TR
TR is the common abbreviation for the Textus Receptus, a historically influential printed Greek New Testament text that underlies many early Protestant Bible translations.
-
D.
TR
TR is the postcode area covering Truro and much of Cornwall in southwest England.
-
E.
RL
RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02586b25c819083c409ce324268cc |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e2196e08190a38e1c6871e71acd |
completed | March 22, 2026, 11:41 p.m. |
| NEDg | Description generation | batch_69c088eaf20c8190a8ed785ebab047af |
completed | March 23, 2026, 12:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c08945dd48819096453dc14fda13d0 |
completed | March 23, 2026, 12:28 a.m. |
Created at: March 22, 2026, 3:48 p.m.