Triple
T36891814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JPMorgan Chase Tower |
E911764
|
entity |
| Predicate | hasStoriesAboveGround |
P995
|
FINISHED |
| Object | 75 |
—
|
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: 75 | Statement: [JPMorgan Chase Tower, hasStoriesAboveGround, 75]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStoriesAboveGround Context triple: [JPMorgan Chase Tower, hasStoriesAboveGround, 75]
-
A.
tellsStoriesIn
Indicates that one entity narrates or recounts stories within or to the context of another entity (such as a place, group, or medium).
-
B.
numberOfStories
chosen
Indicates the total count of levels or floors that a structure or building has.
-
C.
hasBackupStories
Indicates that an entity maintains additional, alternative stories or narratives that can be used if the primary ones fail or are unavailable.
-
D.
hasStandaloneTales
Indicates that an entity includes or is associated with independent, self-contained stories that can be understood without relying on a larger narrative.
-
E.
originStoryIncludes
Indicates that an entity’s origin story contains, involves, or features the referenced element as a component or part of that backstory.
- 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_69f76e8335908190b77e7e11d0e80820 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a005e8a2f7c819085bfc6f04b866d87 |
completed | May 10, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_6a005de82ef08190a015b385d1d3443c |
completed | May 10, 2026, 10:28 a.m. |
Created at: May 3, 2026, 4:13 p.m.