Triple
T34749477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meta headquarters complex |
E1001726
|
entity |
| Predicate | employerBrandingElement |
P156000
|
FINISHED |
| Object | Hacker Way street name |
—
|
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: Hacker Way street name | Statement: [Meta headquarters complex, employerBrandingElement, Hacker Way street name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerBrandingElement Context triple: [Meta headquarters complex, employerBrandingElement, Hacker Way street name]
-
A.
employerBrandingFor
Indicates that one entity develops, manages, or represents the employer brand or employer reputation on behalf of another entity.
-
B.
typicalEmployerBrand
Indicates that an entity is the employer brand that is most commonly or characteristically associated with another entity.
-
C.
employerService
Indicates that one entity provides employment-related services or functions to another entity, typically in the role of an employer.
-
D.
notableEmployerFeature
chosen
Indicates that an employer is distinguished or recognized for a particular characteristic, quality, or attribute.
-
E.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
- 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_69f76db0367081909b57c50a7fb03025 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 3:59 p.m.