Triple
T22206591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forney Lake |
E548823
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Dallas, 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: Dallas, Texas | Statement: [Forney Lake, locatedNear, Dallas, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dallas, Texas Context triple: [Forney Lake, locatedNear, Dallas, Texas]
-
A.
Dallas, Texas
chosen
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.
-
B.
Dallas
Dallas is a popular American comic strip created by cartoonist Jim Davis.
-
C.
Dallas
Dallas is a unisex given name of English origin that has become popular in various English-speaking countries.
-
D.
Dallas
Dallas is a central female character in the classic Western film "Stagecoach," portrayed as a compassionate yet socially ostracized woman whose journey reveals themes of dignity and redemption.
-
E.
Dallas
Dallas is a small borough in northeastern Pennsylvania known as part of the suburban and educational hub of the Wyoming Valley near Wilkes-Barre.
- 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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b2868d88190af313b862fe9d8f2 |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.