Triple
T37770554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David North |
E941534
|
entity |
| Predicate | frequentAssociate |
P177012
|
FINISHED |
| Object | Wolverine |
—
|
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: Wolverine | Statement: [David North, frequentAssociate, Wolverine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentAssociate Context triple: [David North, frequentAssociate, Wolverine]
-
A.
frequentPartner
Indicates that two entities regularly engage in a shared activity or interaction together more often than with others.
-
B.
frequentPatron
Indicates that one entity regularly and repeatedly visits, uses, or patronizes another entity (such as a place, service, or establishment).
-
C.
frequentlySeen
chosen
Indicates that one entity is observed or encountered many times or on a regular basis in relation to another entity.
-
D.
isFrequentAmong
Indicates that something occurs with relatively high frequency within a specified group or set.
-
E.
frequentlyUsedBy
Indicates that something is regularly or commonly utilized by a particular 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_69f76ee4431881908f87e8892a9f39f3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.