Triple
T22802584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Devil’s Hairpin |
E564436
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Jodie Copelan
Jodie Copelan was an American film editor known for her work on mid-20th-century Hollywood features.
|
E1562912
|
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: Jodie Copelan | Statement: [The Devil’s Hairpin, editedBy, Jodie Copelan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jodie Copelan Context triple: [The Devil’s Hairpin, editedBy, Jodie Copelan]
-
A.
Jodie Wolfe
Jodie Wolfe is the central character of the film "Take It Back," around whom the story’s main conflicts and developments revolve.
-
B.
Andrea McArdle
Andrea McArdle is an American actress and singer best known for originating the title role in the Broadway musical "Annie."
-
C.
Lindsay Pearce
Lindsay Pearce is an American actress and singer best known for her appearances on "The Glee Project" and "Glee," as well as for her work in musical theatre.
-
D.
Kerri Gowler
Kerri Gowler is a New Zealand rower and Olympic champion known for her success in women's pair and eight events on the world stage.
-
E.
Kimberlea Cloughley
Kimberlea Cloughley is an American photographer best known for her marriage to actor Tommy Lee Jones.
- 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: Jodie Copelan Triple: [The Devil’s Hairpin, editedBy, Jodie Copelan]
Generated description
Jodie Copelan was an American film editor known for her work on mid-20th-century Hollywood features.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jodie Copelan Target entity description: Jodie Copelan was an American film editor known for her work on mid-20th-century Hollywood features.
-
A.
Jodie Wolfe
Jodie Wolfe is the central character of the film "Take It Back," around whom the story’s main conflicts and developments revolve.
-
B.
Andrea McArdle
Andrea McArdle is an American actress and singer best known for originating the title role in the Broadway musical "Annie."
-
C.
Lindsay Pearce
Lindsay Pearce is an American actress and singer best known for her appearances on "The Glee Project" and "Glee," as well as for her work in musical theatre.
-
D.
Kerri Gowler
Kerri Gowler is a New Zealand rower and Olympic champion known for her success in women's pair and eight events on the world stage.
-
E.
Kimberlea Cloughley
Kimberlea Cloughley is an American photographer best known for her marriage to actor Tommy Lee Jones.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cdf1e308190a05d0f61856be544 |
completed | April 29, 2026, 3:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bca0266b08190976d6fda00720bd3 |
completed | May 19, 2026, 2:25 a.m. |
| NEDg | Description generation | batch_6a0bcb094b60819090c7550dad826fac |
completed | May 19, 2026, 2:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bcb7ccc4881909fe70749449c0e6c |
completed | May 19, 2026, 2:31 a.m. |
Created at: April 17, 2026, 3:31 p.m.