Triple
T12588134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birhor |
E300520
|
entity |
| Predicate | productSpecialization |
P105583
|
FINISHED |
| Object | ropes |
—
|
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: ropes | Statement: [Birhor, productSpecialization, ropes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productSpecialization Context triple: [Birhor, productSpecialization, ropes]
-
A.
marketSpecialization
Indicates a relationship where an entity focuses its activities, products, or services on serving a specific segment or niche of a broader market.
-
B.
producerCharacteristic
Indicates a relationship where a producer is associated with a particular attribute, quality, or trait that characterizes them or their production.
-
C.
creatorSpecialization
Indicates the specific field, discipline, or area of expertise in which a creator primarily works or is specialized.
-
D.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
E.
shopSpecialty
Indicates that a shop primarily focuses on or is specially known for offering a particular type of product or service.
- F. None of above. chosen
Provenance (4 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954e351f88190869220d46e0ce282 |
completed | April 10, 2026, 7:52 p.m. |
Created at: April 9, 2026, 5:06 p.m.