Triple
T3922816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gila Cliff Dwellings (core archeological area) |
E93200
|
entity |
| Predicate | numberOfCavesUsed |
P10755
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Gila Cliff Dwellings (core archeological area), numberOfCavesUsed, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCavesUsed Context triple: [Gila Cliff Dwellings (core archeological area), numberOfCavesUsed, 6]
-
A.
cavesUsedFor
Indicates that certain caves are utilized for a particular purpose, activity, or function by an entity.
-
B.
hasCaves
chosen
Indicates that one entity possesses, contains, or is characterized by the presence of caves.
-
C.
numberOfTunnels
Indicates the quantity of tunnels associated with or passing through a given entity or location.
-
D.
numberOfChambers
Indicates the count of distinct chambers or compartments associated with an entity.
-
E.
numberOfCorridors
Indicates the total count of corridors associated with or contained within a given entity or structure.
- 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_69aed96bfa1081908f7b30f2c647dee6 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeed7c2c848190a6d62e2df9b942d4 |
completed | March 9, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69aee7609c4081908000ce12ae827c3f |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.