Triple
T32512456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uncle Moe’s Family Feedbag |
E830972
|
entity |
| Predicate | previousBusinessNameAtLocation |
P196114
|
FINISHED |
| Object | Moe’s Tavern |
—
|
NE NERFINISHED |
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: Moe’s Tavern | Statement: [Uncle Moe’s Family Feedbag, previousBusinessNameAtLocation, Moe’s Tavern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousBusinessNameAtLocation Context triple: [Uncle Moe’s Family Feedbag, previousBusinessNameAtLocation, Moe’s Tavern]
-
A.
previousLocationName
Indicates that one entity specifies the name of a location where another entity was situated or occurred before its current location.
-
B.
formerSiteName
chosen
Indicates that an entity previously had a different site name, specifying what that earlier name was.
-
C.
employerPredecessorName
Indicates that the referenced name identifies a previous employer of the entity in question.
-
D.
previousFranchiseLocation
Indicates that one franchise location directly preceded another in time or sequence within the same franchise.
-
E.
businessName
Indicates that one entity is the official or recognized business name of another entity.
- F. None of above.
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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fec00f27988190955de6b6348a4d97 |
completed | May 9, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69febd52037c8190b475dbd50fdbc13e |
completed | May 9, 2026, 4:51 a.m. |
Created at: May 1, 2026, 1 a.m.