Triple
T34964310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hancock Tower |
E1008346
|
entity |
| Predicate | rankByHeightInUS |
P153860
|
FINISHED |
| Object | one of the tallest buildings in the United States |
—
|
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: one of the tallest buildings in the United States | Statement: [Hancock Tower, rankByHeightInUS, one of the tallest buildings in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByHeightInUS Context triple: [Hancock Tower, rankByHeightInUS, one of the tallest buildings in the United States]
-
A.
rankAmongTallestInUS
chosen
Indicates that the entity is among the tallest of its kind within the United States.
-
B.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
C.
countryRankByHeight
Indicates the relative position of a country when countries are ordered by the height of something (e.g., average elevation, tallest point, or average citizen height).
-
D.
countryRankByHeightAtCompletion
Indicates the position of a country in an ordered list based on the height of something (typically a structure or project) at the time it was completed.
-
E.
rankingByHeightInJapan
Indicates the relative order of entities based on their height specifically within the context of Japan.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.