Triple
T1216251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph LaShelle |
E26112
|
entity |
| Predicate | workedOn |
P3
|
FINISHED |
| Object |
Laura
Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
|
E168229
|
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: Laura | Statement: [Joseph LaShelle, workedOn, Laura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Context triple: [Joseph LaShelle, workedOn, Laura]
-
A.
Laura
Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
-
B.
Lisa
Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
-
C.
Laurene
Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
-
D.
Kathleen
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
-
E.
Kathleen
"Kathleen" is a punk rock song by the American band Pinhead Gunpowder, known for its raw, melodic style and association with the East Bay punk scene.
- 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: Laura Triple: [Joseph LaShelle, workedOn, Laura]
Generated description
Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laura Target entity description: Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
-
A.
Laura
Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
-
B.
Lisa
Lisa is a central character in the science fiction adventure film "Zathura: A Space Adventure," where she becomes unwittingly involved in her younger brothers' perilous journey through outer space.
-
C.
Laurene
Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
-
D.
Kathleen
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
-
E.
Kathleen
"Kathleen" is a punk rock song by the American band Pinhead Gunpowder, known for its raw, melodic style and association with the East Bay punk scene.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be059c5c8190a200f09442c22334 |
completed | March 1, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad158eca208190b763da8cb9af1dcd |
completed | March 8, 2026, 6:22 a.m. |
| NEDg | Description generation | batch_69ad15f77e448190ac68777035c1559b |
completed | March 8, 2026, 6:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad165bf0308190bc7fbb1438806d1a |
completed | March 8, 2026, 6:25 a.m. |
Created at: March 1, 2026, 7:46 p.m.