Triple
T8704171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barney |
E206604
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Bernie |
E137063
|
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: Bernie | Statement: [Barney, hasRelatedName, Bernie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernie Context triple: [Barney, hasRelatedName, Bernie]
-
A.
Bernie
chosen
Bernie is a common diminutive form of the given name Bernard, often used as a familiar or informal nickname.
-
B.
Weiner
Weiner is a surname of Germanic origin borne by various notable individuals across fields such as business, politics, and entertainment.
-
C.
Bernie Sanders
Bernie Sanders is a longtime U.S. senator from Vermont and prominent progressive politician known for championing democratic socialism, economic equality, and universal healthcare.
-
D.
Bernie Dodd
Bernie Dodd is a driven Broadway director in the film "The Country Girl," whose demanding methods and personal struggles shape the story’s central drama.
-
E.
Connell
Connell is a surname of Irish origin borne by various notable individuals across literature, sports, and public life.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58fa0a208190a520e0e1f7faaea9 |
completed | March 31, 2026, 11:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef41e3ec08190b29adf483cdf8cc3 |
completed | April 2, 2026, 10:56 p.m. |
Created at: March 30, 2026, 6:34 p.m.