Triple
T29988691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GE Lighting |
E761802
|
entity |
| Predicate | hasBrandReputationFor |
P73564
|
FINISHED |
| Object | reliability |
—
|
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: reliability | Statement: [GE Lighting, hasBrandReputationFor, reliability]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandReputationFor Context triple: [GE Lighting, hasBrandReputationFor, reliability]
-
A.
hasBrandReputation
chosen
Indicates that an entity possesses a certain level or type of perceived quality, trustworthiness, or public image associated with its brand.
-
B.
usesBrandReputationOf
Indicates that one entity leverages or capitalizes on the brand reputation of another entity for its own purposes.
-
C.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
D.
manufacturerReputation
Indicates the perceived reliability, quality, and trustworthiness associated with a product’s manufacturer.
-
E.
hasBrandRecognitionFor
Indicates that one entity is aware of, recognizes, or can identify the brand 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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 29, 2026, 6:37 p.m.