Triple
T6715600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roland Garros Airport |
E153258
|
entity |
| Predicate | hasFlightConnection |
P23780
|
FINISHED |
| Object | Chennai |
E12324
|
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: Chennai | Statement: [Roland Garros Airport, hasFlightConnection, Chennai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chennai Context triple: [Roland Garros Airport, hasFlightConnection, Chennai]
-
A.
Chennai
chosen
Chennai is a major coastal metropolis in southern India, serving as the capital of Tamil Nadu and a key cultural, economic, and automotive hub.
-
B.
Tiruchirappalli
Tiruchirappalli is a major city in the Indian state of Tamil Nadu, known for its historic temples, educational institutions, and strategic location along the Kaveri River.
-
C.
Madras
Madras is a small city in central Oregon known as an agricultural hub and gateway to outdoor recreation in the surrounding high desert region.
-
D.
Madras
Madras is an unincorporated community located in Coweta County in the U.S. state of Georgia.
-
E.
Coimbatore
Coimbatore is a major industrial and educational city in the Indian state of Tamil Nadu, known especially for its textile, engineering, and manufacturing industries.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d7c94bac8190ae4b236d1b04bec9 |
completed | March 27, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70af6d1608190887c5d9f94ffe9fa |
completed | March 27, 2026, 10:55 p.m. |
Created at: March 27, 2026, 2:07 p.m.