Triple
T13753639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carla Tortelli |
E330418
|
entity |
| Predicate | worksAt |
P7
|
FINISHED |
| Object | Cheers bar |
E325134
|
NE FINISHED |
How this triple was built (2 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: Cheers bar | Statement: [Carla Tortelli, worksAt, Cheers bar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheers bar Context triple: [Carla Tortelli, worksAt, Cheers bar]
-
A.
Cheers bar
chosen
Cheers bar is the iconic Boston neighborhood pub that serves as the central gathering place for the characters in the classic television sitcom "Cheers."
-
B.
The Rooster Bar
The Rooster Bar is a legal thriller novel by bestselling American author John Grisham that follows law students entangled in a predatory student-loan and for-profit law school scheme.
-
C.
Chat ‘N’ Chill beach bar
Chat ‘N’ Chill beach bar is a laid-back, open-air beachfront spot in Exuma known for its casual island vibe, fresh conch salad, and opportunities to swim with friendly stingrays.
-
D.
All Bar One
All Bar One is a UK-based chain of stylish city-centre bars known for serving cocktails, wine, and modern pub food in a contemporary setting.
-
E.
Bacchus Lounge
Bacchus Lounge is a themed bar and lounge within the Shanghai Disneyland Hotel offering drinks and light refreshments in a relaxed, Disney-inspired setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0215cfa08190aaed8b089aff217b |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b06d9fd48190a10b86a0d68fac70 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:09 p.m.