Triple
T37226587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hokey Wolf |
E923019
|
entity |
| Predicate | oftenSeen |
P177012
|
FINISHED |
| Object | hatching schemes |
—
|
LITERAL 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: hatching schemes | Statement: [Hokey Wolf, oftenSeen, hatching schemes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenSeen Context triple: [Hokey Wolf, oftenSeen, hatching schemes]
-
A.
frequentlySeen
chosen
Indicates that one entity is observed or encountered many times or on a regular basis in relation to another entity.
-
B.
oftenHave
Indicates that one entity frequently possesses, experiences, or is associated with another entity.
-
C.
oftenSoughtOn
Indicates that one entity is frequently searched for, requested, or pursued in relation to another entity.
-
D.
oftenFrom
Indicates that something frequently originates, derives, or comes from a particular source or location.
-
E.
oftenSetIn
Indicates that something, such as a story or event, frequently takes place within a particular setting or context.
- 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
Created at: May 3, 2026, 4:15 p.m.