Triple
T14739166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciociaria |
E346295
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Liri |
E1002502
|
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: Liri | Statement: [Ciociaria, hasRiver, Liri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liri Context triple: [Ciociaria, hasRiver, Liri]
-
A.
Liri
chosen
Liri is a river in central Italy that flows through the regions of Lazio and Campania before joining the Gari to form the Garigliano.
-
B.
Yulu
Yulu is a Central Sudanic language spoken by the Yulu people primarily in parts of South Sudan and the Central African Republic.
-
C.
Lusei
Lusei are a major clan of the Mizo people of Northeast India, historically influential in shaping Mizo culture, language, and social organization.
-
D.
Liat
Liat is a young Tonkinese woman in the Rodgers and Hammerstein musical "South Pacific," whose romantic relationship with an American lieutenant highlights the themes of love and cultural conflict.
-
E.
Oizys
Oizys is the Greek personification of misery, distress, and wretchedness, traditionally regarded as a dark and sorrowful deity.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec73264848190be23c5f0260cbe13 |
completed | April 14, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb91fdf88190bdcc9a93289f6b7f |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.