Triple
T30932816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scranton branch |
E788040
|
entity |
| Predicate | hasSalesmanCharacter |
P139519
|
FINISHED |
| Object | Jim Halpert |
—
|
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: Jim Halpert | Statement: [Scranton branch, hasSalesmanCharacter, Jim Halpert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSalesmanCharacter Context triple: [Scranton branch, hasSalesmanCharacter, Jim Halpert]
-
A.
sellsToCharacter
Indicates that one entity sells goods or services to a specific character.
-
B.
hasSalesComponent
Indicates that something includes, involves, or is associated with a sales-related element or function.
-
C.
hasRetailCharacteristic
Indicates that an entity possesses a specific attribute, feature, or quality relevant to retail contexts (such as pricing, packaging, or point-of-sale properties).
-
D.
hasStockCharacter
chosen
Indicates that a work of fiction includes a stereotypical or commonly recurring character type as part of its cast.
-
E.
hasConcessionaire
Indicates that one entity is designated as the concessionaire (holder of operating or usage rights under a concession) for 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 29, 2026, 8:52 p.m.