Triple
T17102387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tama area |
E415010
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Inagi |
E197984
|
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: Inagi | Statement: [Tama area, hasPart, Inagi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inagi Context triple: [Tama area, hasPart, Inagi]
-
A.
Inagi
chosen
Inagi is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama River.
-
B.
Anogi
Anogi is a small traditional mountain village on the Greek island of Ithaca, known for its historic church, stone houses, and panoramic views.
-
C.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
-
D.
Nishiizu
Nishiizu is a coastal town in Shizuoka Prefecture, Japan, known for its rugged seaside scenery, hot springs, and views of Suruga Bay.
-
E.
Ogiso
Ogiso is the traditional title of the early divine kings of the ancient Benin kingdom, ruling the realm known as Igodomigodo before the rise of the Oba dynasty.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc239a088190a776fe0f4361ffc7 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139fdda488190a1ca5c7ca875e044 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.