Triple
T15265536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conflent |
E364891
|
entity |
| Predicate | traversedByRiver |
P165
|
FINISHED |
| Object | Têt |
E85350
|
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: Têt | Statement: [Conflent, traversedByRiver, Têt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Têt Context triple: [Conflent, traversedByRiver, Têt]
-
A.
Têt
chosen
The Têt is a river in southern France that flows through the Pyrénées-Orientales department in the Occitanie region before reaching the Mediterranean Sea.
-
B.
Yennayer
Yennayer is the Amazigh (Berber) New Year, a traditional North African celebration marked by cultural rituals, feasts, and community gatherings.
-
C.
Spring Festival
The Spring Festival is the most important traditional Chinese New Year celebration, marked by family reunions, festive meals, cultural rituals, and the welcoming of the lunar new year.
-
D.
Zhoshi festival
Zhoshi festival is a traditional spring celebration of the Kalash people in Pakistan’s Chitral region, marking the arrival of the new agricultural year with rituals, music, and dance.
-
E.
Chūnxī Lù
Chūnxī Lù is a major commercial and shopping street in Chengdu, China, known for its bustling retail scene and modern urban atmosphere.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00851c5b88190a296b6a105d3ee30 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee600340c8190a1888d35c2c1bc86 |
completed | May 9, 2026, 7:45 a.m. |
Created at: April 10, 2026, 3:14 a.m.