Triple
T3017856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pitfall |
E82379
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Louis Forbes
Louis Forbes was a film composer and music director known for scoring numerous Hollywood productions during the mid-20th century.
|
E321153
|
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: Louis Forbes | Statement: [Pitfall, musicBy, Louis Forbes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Louis Forbes Context triple: [Pitfall, musicBy, Louis Forbes]
-
A.
Frederick Winsor
Frederick Winsor was a pioneering British physician and medical officer known for his contributions to public health and military medicine in the 19th century.
-
B.
Robert Fabyan
Robert Fabyan was an early 16th-century English chronicler and London alderman best known for his historical compilation "Fabyan's Chronicle," which combined English and French histories.
-
C.
Walter Brewster
Walter Brewster was a prominent local landowner and early settler after whom the Village of Brewster in New York was named.
-
D.
James Fawcett
James Fawcett was an architect best known for co-designing Melbourne’s iconic Flinders Street Station.
-
E.
Robert Gossett
Robert Gossett is an American actor best known for his role as Commander Russell Taylor on the television crime drama series "The Closer."
- 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: Louis Forbes Triple: [Pitfall, musicBy, Louis Forbes]
Generated description
Louis Forbes was a film composer and music director known for scoring numerous Hollywood productions during the mid-20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Louis Forbes Target entity description: Louis Forbes was a film composer and music director known for scoring numerous Hollywood productions during the mid-20th century.
-
A.
Frederick Winsor
Frederick Winsor was a pioneering British physician and medical officer known for his contributions to public health and military medicine in the 19th century.
-
B.
Robert Fabyan
Robert Fabyan was an early 16th-century English chronicler and London alderman best known for his historical compilation "Fabyan's Chronicle," which combined English and French histories.
-
C.
Walter Brewster
Walter Brewster was a prominent local landowner and early settler after whom the Village of Brewster in New York was named.
-
D.
James Fawcett
James Fawcett was an architect best known for co-designing Melbourne’s iconic Flinders Street Station.
-
E.
Robert Gossett
Robert Gossett is an American actor best known for his role as Commander Russell Taylor on the television crime drama series "The Closer."
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a90ea64819080620e60bbd6aa24 |
completed | March 8, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dea9a7c4819087fb6853d839fb1e |
completed | March 11, 2026, 9:29 p.m. |
| NEDg | Description generation | batch_69b1df92c05481908f4490412b5c4885 |
completed | March 11, 2026, 9:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1dfe4bfe481909ebd745964940294 |
completed | March 11, 2026, 9:34 p.m. |
Created at: March 8, 2026, 3 p.m.