Triple
T159770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lerner family |
E3256
|
entity |
| Predicate | notableBusiness |
P22
|
FINISHED |
| Object | shopping centers |
—
|
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: shopping centers | Statement: [Lerner family, notableBusiness, shopping centers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableBusiness Context triple: [Lerner family, notableBusiness, shopping centers]
-
A.
notableFor
chosen
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
notableSingle
Indicates that the subject is particularly recognized or distinguished for one specific, individual instance (such as a single work, event, or achievement).
-
C.
notableAsset
Indicates that an entity possesses or is associated with an asset that is particularly significant, prominent, or noteworthy in relation to it.
-
D.
notableProduct
Indicates that a product is especially significant, prominent, or well-known in relation to the associated entity.
-
E.
notablePrimary
Indicates that one entity is the main or most prominent example, instance, or representative of another 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25855baf48190a1b63f2e5865d957 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a25660c2a48190b4174d5e6da3cb9d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.