Triple
T21125852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dublin Area Rapid Transit |
E520553
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | Luas |
E253338
|
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: Luas | Statement: [Dublin Area Rapid Transit, connectsWith, Luas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luas Context triple: [Dublin Area Rapid Transit, connectsWith, Luas]
-
A.
Luas
chosen
Luas is Dublin’s modern light rail tram system, providing frequent urban and suburban public transport across the city and its surrounding areas.
-
B.
Lahan
Lahan is a municipality and commercial hub in southeastern Nepal known for its role as a regional trade and transport center.
-
C.
Lanahan
Lanahan is a surname most notably associated with American lawyer and politician Samuel Jackson Lanahan.
-
D.
Taman
Taman is a Nilo-Saharan language spoken by the Taman people in parts of Chad and Sudan.
-
E.
Taman
Taman is a rural settlement on Russia’s Taman Peninsula, near the Black Sea and the Kerch Strait, known for its historical ties to ancient Greek colonies and strategic coastal location.
- 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72238cf708190a4676c40deea2e46 |
completed | April 21, 2026, 7:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0965eb985081908e83e65d104e25ee |
completed | May 17, 2026, 6:53 a.m. |
Created at: April 16, 2026, 2:56 p.m.