Triple
T26111382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marilyn Monroe Towers |
E658704
|
entity |
| Predicate | tower1Floors |
P76776
|
FINISHED |
| Object | 56 |
—
|
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: 56 | Statement: [Marilyn Monroe Towers, tower1Floors, 56]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tower1Floors Context triple: [Marilyn Monroe Towers, tower1Floors, 56]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
C.
hasOfficeFloors
Indicates that one entity (typically a building or structure) contains floors that are designated or used as office space.
-
D.
storeysOfTallestTower
chosen
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
E.
locatedInBuildingFloorCount
Indicates that one entity is located in or associated with a building characterized by a specific number of floors.
- 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60c698ae48190871cd445422bad91 |
completed | May 2, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 8:02 p.m.