Triple
T1628563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urban Light |
E35201
|
entity |
| Predicate | isSiteSpecific |
P30375
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Urban Light, isSiteSpecific, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSiteSpecific Context triple: [Urban Light, isSiteSpecific, true]
-
A.
containsSite
Indicates that one entity spatially or structurally includes another entity as a site or location within its bounds.
-
B.
isSiteOf
Indicates that a location or place serves as the setting or host for a particular event, activity, or feature.
-
C.
isTeamSpecific
Indicates that something applies only to, or is restricted to, a particular team rather than being general or shared across multiple teams.
-
D.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
-
E.
coversTypeOfSite
Indicates that one entity provides coverage or applies to a particular category or type of site.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a94319becc819089c2daf45fe08a0c |
completed | March 5, 2026, 8:47 a.m. |
Created at: March 4, 2026, 7:28 p.m.