Triple
T6693622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas urban area |
E152689
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object | Little Elm |
E202944
|
NE 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: Little Elm | Statement: [Dallas urban area, hasSuburb, Little Elm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Little Elm Context triple: [Dallas urban area, hasSuburb, Little Elm]
-
A.
Little Elm, Texas
chosen
Little Elm, Texas is a rapidly growing suburban town in the Dallas–Fort Worth metroplex known for its extensive shoreline along Lewisville Lake and family-oriented community.
-
B.
Rowlett
Rowlett is a suburban city in the Dallas–Fort Worth metropolitan area of Texas, known for its location along Lake Ray Hubbard and family-oriented residential communities.
-
C.
Grand Prairie
Grand Prairie is a mid-sized suburban city in the Dallas–Fort Worth metropolitan area known for its family attractions, parks, and growing residential communities.
-
D.
Duncanville
Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
-
E.
Coppell
Coppell is a suburban city in the Dallas–Fort Worth metropolitan area known for its affluent residential neighborhoods and strong public school system.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6b1955e448190adbfed7dc28f8c52 |
completed | March 27, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8109adff8819081426b44ae70bdfb |
completed | March 28, 2026, 5:32 p.m. |
Created at: March 27, 2026, 2:05 p.m.