Triple
T9872905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Ratzenberger |
E240000
|
entity |
| Predicate | voicedCharacter |
P2000
|
FINISHED |
| Object |
Construction Foreman Tom
Construction Foreman Tom is a minor character in Pixar’s Toy Story franchise, portrayed as a gruff, no-nonsense construction worker involved in the toy characters’ adventures.
|
E826268
|
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: Construction Foreman Tom | Statement: [John Ratzenberger, voicedCharacter, Construction Foreman Tom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Construction Foreman Tom Context triple: [John Ratzenberger, voicedCharacter, Construction Foreman Tom]
-
A.
Foreman
Foreman is an open-source lifecycle management and provisioning tool for physical and virtual servers, commonly used to automate system configuration and deployment.
-
B.
Big Tom
Big Tom is a prominent mountain peak in the Black Mountains of North Carolina, known for its rugged terrain and scenic hiking routes.
-
C.
TOM
TOM is the ICAO airline designator used to identify TUI Airways in international aviation operations.
-
D.
TOM
TOM is the National Rail station code assigned to Tottenham Hale railway station in London, England.
-
E.
Tommy Tar
Tommy Tar is the official mascot character representing the Tars athletic teams.
- 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: Construction Foreman Tom Triple: [John Ratzenberger, voicedCharacter, Construction Foreman Tom]
Generated description
Construction Foreman Tom is a minor character in Pixar’s Toy Story franchise, portrayed as a gruff, no-nonsense construction worker involved in the toy characters’ adventures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Construction Foreman Tom Target entity description: Construction Foreman Tom is a minor character in Pixar’s Toy Story franchise, portrayed as a gruff, no-nonsense construction worker involved in the toy characters’ adventures.
-
A.
Foreman
Foreman is an open-source lifecycle management and provisioning tool for physical and virtual servers, commonly used to automate system configuration and deployment.
-
B.
Big Tom
Big Tom is a prominent mountain peak in the Black Mountains of North Carolina, known for its rugged terrain and scenic hiking routes.
-
C.
TOM
TOM is the ICAO airline designator used to identify TUI Airways in international aviation operations.
-
D.
TOM
TOM is the National Rail station code assigned to Tottenham Hale railway station in London, England.
-
E.
Tommy Tar
Tommy Tar is the official mascot character representing the Tars athletic teams.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f754008190abe3fe034b42908e |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e46f18148190a36af7e7d7487205 |
completed | April 5, 2026, 4:26 a.m. |
| NEDg | Description generation | batch_69d1e52132188190ad96780fd75dfa1b |
completed | April 5, 2026, 4:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1e57697a08190a3608f5ad6e306f1 |
completed | April 5, 2026, 4:30 a.m. |
Created at: March 30, 2026, 8:37 p.m.