Triple
T6693595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas urban area |
E152689
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object | Lancaster |
E114102
|
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: Lancaster | Statement: [Dallas urban area, hasSuburb, Lancaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lancaster Context triple: [Dallas urban area, hasSuburb, Lancaster]
-
A.
Lancaster
Lancaster is a historic city in North West England known for its medieval castle, Georgian architecture, and role as the county town of Lancashire.
-
B.
Lancaster
chosen
Lancaster is a city in northern Los Angeles County, California, known for its location in the Antelope Valley of the Mojave Desert and its aerospace and renewable energy industries.
-
C.
Lancaster
Lancaster is a small community in eastern Ontario, Canada, located near the Quebec border along the St. Lawrence River.
-
D.
Lancaster
Lancaster was the original settlement that later developed into the city of Lincoln, the capital of Nebraska.
-
E.
Lancaster
Lancaster is an English surname most famously associated with the American actor Burt Lancaster.
- 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_69c6f7b97210819086e88624c476fa24 |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:05 p.m.