Triple
T3835945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2 World Trade Center |
E91131
|
entity |
| Predicate | plannedNumberOfStories |
P995
|
FINISHED |
| Object | over 80 |
—
|
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 80 | Statement: [2 World Trade Center, plannedNumberOfStories, over 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedNumberOfStories Context triple: [2 World Trade Center, plannedNumberOfStories, over 80]
-
A.
numberOfStories
chosen
Indicates the total count of levels or floors that a structure or building has.
-
B.
plannedNumberOfTests
Indicates the total count of tests that are intended or scheduled to be conducted for a given context or period.
-
C.
numberOfRulesPlanned
Indicates the planned or intended count of rules associated with an entity or process.
-
D.
storyNumber
Indicates the numerical identifier assigned to a specific story within a collection, sequence, or dataset.
-
E.
plannedHeight
Indicates the intended or designed vertical size or elevation that something is planned to have.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb9a27508190b05e5312cc7c8033 |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.