Triple
T35386058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Weston |
E1022795
|
entity |
| Predicate | hasGoodRelationsWith |
P150269
|
FINISHED |
| Object | the Woodhouse family |
—
|
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: the Woodhouse family | Statement: [Mr. Weston, hasGoodRelationsWith, the Woodhouse family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGoodRelationsWith Context triple: [Mr. Weston, hasGoodRelationsWith, the Woodhouse family]
-
A.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
B.
hasNeighborRelationshipWith
Indicates that one entity is located adjacent to or directly next to another entity, sharing a neighbor relationship.
-
C.
hasFriendshipPactWith
Indicates a mutual agreement or bond of friendship established between two entities.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
hasSocialTieWith
chosen
Indicates a social relationship or connection exists between two entities, such as friendship, acquaintance, or other interpersonal tie.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f50080819095ff3c2cefc74fea |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.