Triple
T20101768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ميناء الحديدة |
E496560
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | الحديدة |
—
|
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: الحديدة | Statement: [ميناء الحديدة, locatedIn, الحديدة]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: الحديدة Context triple: [ميناء الحديدة, locatedIn, الحديدة]
-
A.
الحديدة
chosen
الحديدة هي مدينة ساحلية يمنية كبرى تقع على البحر الأحمر وتعد من أهم موانئ اليمن ومراكزه التجارية.
-
B.
Irongron
Irongron is a brutish, ambitious medieval warlord who serves as the main human antagonist in the Doctor Who serial "The Time Warrior."
-
C.
Maden
Maden is a 1978 Turkish social realist film directed by Yavuz Özkan, known for its portrayal of coal miners’ struggles and featuring a leading performance by Tarık Akan.
-
D.
Maden
Maden is a town and district in eastern Turkey known historically for its mining activities and mountainous terrain.
-
E.
Laurium
Laurium is an ancient mining town in southeastern Attica, Greece, historically renowned for its rich silver mines that financed Athenian power in the classical period.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66670a5b48190afe06c8a582bba3d |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:27 p.m.