Triple
T27151835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PAO |
E682408
|
entity |
| Predicate | isNearTechnologyHub |
P162515
|
FINISHED |
| Object | Silicon Valley |
—
|
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: Silicon Valley | Statement: [PAO, isNearTechnologyHub, Silicon Valley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNearTechnologyHub Context triple: [PAO, isNearTechnologyHub, Silicon Valley]
-
A.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
B.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
C.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
D.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
-
E.
connectsToUrbanCenter
Indicates that one entity has a direct or functional linkage to an urban center, such as through infrastructure, services, or regular interaction.
- F. None of above. chosen
Provenance (4 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f625402d808190be8279d895d2b27f |
completed | May 2, 2026, 4:24 p.m. |
Created at: April 27, 2026, 9:14 a.m.