Triple
T10310085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pueblo Bonito |
E241864
|
entity |
| Predicate | hasMaximumStories |
P995
|
FINISHED |
| Object | four or more stories |
—
|
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: four or more stories | Statement: [Pueblo Bonito, hasMaximumStories, four or more stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaximumStories Context triple: [Pueblo Bonito, hasMaximumStories, four or more stories]
-
A.
numberOfStories
chosen
Indicates the total count of levels or floors that a structure or building has.
-
B.
seriesLengthMaximum
Indicates the maximum allowable or observed length (e.g., number of items or installments) in a series.
-
C.
talesCount
Indicates the number of tales associated with or attributed to a given entity.
-
D.
hasCanonicalNumberOfArticles
Indicates that an entity is associated with a standard, officially recognized count of articles that define or describe it.
-
E.
hasInfluentialStory
Indicates that one entity possesses or is associated with a story that significantly shapes, impacts, or guides the beliefs, actions, or development of another entity.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:47 a.m.