Triple
T33951490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Powell |
E870451
|
entity |
| Predicate | worldRecordCity |
P196157
|
FINISHED |
| Object | Tokyo |
—
|
NE NERFINISHED |
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: Tokyo | Statement: [Mike Powell, worldRecordCity, Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldRecordCity Context triple: [Mike Powell, worldRecordCity, Tokyo]
-
A.
citySigned
Indicates that a city has formally signed or endorsed an agreement, document, or commitment.
-
B.
nearestLargeUrbanArea
Indicates that one entity is the closest major city or large urban center to the other entity.
-
C.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
D.
isGlobalCity
Indicates that a city holds significant worldwide influence in areas such as economics, culture, politics, or connectivity, making it an important node in the global system.
-
E.
hasHighestUrbanizationRateIn
Indicates that the subject has the greatest proportion of its population living in urban areas compared to all other entities within the specified object region or group.
- F. None of above. chosen
Provenance (4 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_69f3499c2d7481909c953a5010227725 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
| PDg | Predicate description generation | batch_69fe0d14778c8190986fa4f37f992a2f |
completed | May 8, 2026, 4:19 p.m. |
Created at: May 1, 2026, 1:49 a.m.