Triple
T29987420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 200 Public Square |
E761767
|
entity |
| Predicate | rankInClevelandByHeight |
P27607
|
FINISHED |
| Object | one of the tallest buildings in Cleveland |
—
|
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 Cleveland | Statement: [200 Public Square, rankInClevelandByHeight, one of the tallest buildings in Cleveland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInClevelandByHeight Context triple: [200 Public Square, rankInClevelandByHeight, one of the tallest buildings in Cleveland]
-
A.
rankInCityByHeight
chosen
Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
-
B.
rankAmongTallestInUS
Indicates that the entity is among the tallest of its kind within the United States.
-
C.
rankAmongTallestBuildings
Indicates that one building is among the tallest buildings within a specified group, area, or category.
-
D.
populationRankInOhio
Indicates the relative ranking of an entity’s population size compared to other entities within the state of Ohio.
-
E.
rankingByHeightInSriLanka
Indicates an ordering of entities based on their relative heights specifically within the context of Sri Lanka.
- 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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 29, 2026, 6:37 p.m.