Triple
T23194675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humen Forts |
E579841
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Dazhisha Fort |
—
|
NE NERFINISHED |
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: Dazhisha Fort | Statement: [Humen Forts, hasPart, Dazhisha Fort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dazhisha Fort Context triple: [Humen Forts, hasPart, Dazhisha Fort]
-
A.
Sabi Fortress
Sabi Fortress is a historic defensive stronghold, likely of regional military and cultural significance, associated with the place known as Sabi.
-
B.
Tung Fort
Tung Fort is a hill fort in Maharashtra, India, known for its steep, conical peak and panoramic views over the Pawna Lake region.
-
C.
Anping Fort
Anping Fort is a historic Dutch-built fortress in Tainan, Taiwan, that served as a key colonial stronghold and trading post in the 17th century.
-
D.
Weiyuan Fort
chosen
Weiyuan Fort is a historic coastal defense fortification in Humen, China, best known for its role in guarding the Pearl River estuary during the Opium Wars.
-
E.
Sikayauvati fortress
Sikayauvati fortress was an ancient stronghold known as the site where the usurper Gaumata, who briefly seized the Persian throne, met his death.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fda64cc8190aeb5ccd8d8d20858 |
completed | April 29, 2026, 4:58 a.m. |
Created at: April 17, 2026, 4:06 p.m.