Triple
T13992074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namu |
E336603
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Namu |
E336603
|
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: Namu | Statement: [Namu, hasName, Namu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namu Context triple: [Namu, hasName, Namu]
-
A.
Namu
chosen
Namu is the main settlement and administrative center of Namu Atoll in the Marshall Islands.
-
B.
Namin
Namin is a city in Iran known for its location in the mountainous, historically rich Ardabil region in the northwest of the country.
-
C.
Nambui
Nambui was a Mongol empress consort of the Yuan dynasty and a prominent wife of Kublai Khan, influential in the imperial court after the death of his first empress.
-
D.
Nam-ku
Nam-ku is the McCune–Reischauer romanization of Nam District, an administrative district in the city of Busan, South Korea.
-
E.
Kamsa
Kamsa is a tyrannical king in Hindu mythology, best known as the evil uncle and nemesis of Lord Krishna.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb3b5d881909f15a1e08bb202f3 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac98ca448190b585ef69a4e4bfca |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:19 p.m.