Triple
T22836433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Young |
E565959
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Houston, Texas |
—
|
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: Houston, Texas | Statement: [Michael Young, birthPlace, Houston, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Houston, Texas Context triple: [Michael Young, birthPlace, Houston, Texas]
-
A.
Houston
Houston is a major U.S. metropolis known for its energy industry, NASA’s Johnson Space Center, and its diverse, rapidly growing population.
-
B.
Houston
Houston is a village in Renfrewshire, Scotland, known for its historic conservation area and role as a commuter settlement near Glasgow.
-
C.
Dallas, Texas
Dallas, Texas is a major metropolitan city in northern Texas known for its role as a commercial and cultural hub, particularly in finance, technology, and telecommunications.
-
D.
Houston, Texas, United States
chosen
Houston, Texas, United States is a major Gulf Coast metropolis known for its diverse population, energy industry, NASA’s Johnson Space Center, and influential contributions to American music and culture.
-
E.
Dallas
Dallas is a character appearing in the "Home Invasion" storyline.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2f09608190bc8e465e53b39e2e |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:35 p.m.