Triple
T5093837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Husky |
E114818
|
entity |
| Predicate | socialNeeds |
P15142
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Husky, socialNeeds, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialNeeds Context triple: [Husky, socialNeeds, high]
-
A.
managedSocialAffairsOf
Indicates that one entity was responsible for organizing, overseeing, or conducting the social affairs or social-related activities of another entity.
-
B.
welfareConcern
Indicates that one entity has a concern, issue, or responsibility related to the welfare or well-being of another entity.
-
C.
needBased
Indicates that something is determined, allocated, or provided according to the level of need rather than uniform or fixed criteria.
-
D.
socialConcern
chosen
Indicates a relationship where an entity is concerned about, attentive to, or actively engaged with social issues, problems, or well-being.
-
E.
socialIssue
Indicates a relationship where something is recognized or treated as a problem or concern affecting society or a community at large.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75454920819086e09d6055087e40 |
completed | March 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:40 p.m.