Triple
T35631248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The original Las Vegas |
E1029590
|
entity |
| Predicate | hasNumberOfHistoricBuildings |
P198772
|
FINISHED |
| Object | over 900 |
—
|
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: over 900 | Statement: [The original Las Vegas, hasNumberOfHistoricBuildings, over 900]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfHistoricBuildings Context triple: [The original Las Vegas, hasNumberOfHistoricBuildings, over 900]
-
A.
containsHistoricHouse
Indicates that one entity includes or encompasses a historic house within its boundaries or composition.
-
B.
hasHistoricChurches
Indicates that an entity possesses or contains one or more churches of recognized historical significance.
-
C.
residenceHistoric
Indicates that a residence has historical significance or is formally recognized as a historic dwelling.
-
D.
hasHistoricFurnishings
Indicates that an entity contains or is equipped with furnishings that are of historical origin or significance.
-
E.
hasPreservedBuildings
Indicates that an entity possesses buildings that have been maintained or kept in their original or historical condition.
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff0491409c8190be40f633a58da0b1 |
completed | May 9, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69ff040bb5cc81909534c7eee85d5e90 |
completed | May 9, 2026, 9:53 a.m. |
| PDg | Predicate description generation | batch_69ff04901ab081908b68563836fcdc99 |
completed | May 9, 2026, 9:55 a.m. |
Created at: May 3, 2026, 4:05 p.m.