Triple
T4537131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bar |
E107433
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Old Bar |
E102827
|
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: Old Bar | Statement: [Bar, hasLandmark, Old Bar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Old Bar Context triple: [Bar, hasLandmark, Old Bar]
-
A.
Old Bar
chosen
Old Bar is a small coastal town in New South Wales, Australia, known for its beaches, surfing, and relaxed holiday atmosphere.
-
B.
Old Well
Old Well is an iconic neoclassical rotunda and campus symbol of the University of North Carolina at Chapel Hill, traditionally associated with good luck for students who drink from it.
-
C.
Old Well
Old Well is a 1986 Chinese drama film directed by Wu Tianming and noted for its acclaimed cinematography by Zhang Yimou.
-
D.
Old Mon
Old Mon is an ancient Austroasiatic language historically spoken in what is now Myanmar and Thailand, known from inscriptions that significantly illuminate early mainland Southeast Asian history and culture.
-
E.
Munroe Tavern
Munroe Tavern is a historic 18th-century inn and museum in Lexington, Massachusetts, notable for its role in the American Revolutionary War.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacfb2ba48190b7f1b23785e9d030 |
completed | March 20, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:04 p.m.