Triple
T13010002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Eaton |
E322383
|
entity |
| Predicate | placeOfActivity |
P1527
|
FINISHED |
| Object | Derna |
E50126
|
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: Derna | Statement: [William Eaton, placeOfActivity, Derna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Derna Context triple: [William Eaton, placeOfActivity, Derna]
-
A.
Derna
chosen
Derna is a coastal city in eastern Libya known for its strategic location, turbulent political history, and role as a focal point in the country's conflicts.
-
B.
Derna District
Derna District is an administrative region in eastern Libya centered on the coastal city of Derna, known historically as a Mediterranean port and cultural hub.
-
C.
Marsa al-Brega
Marsa al-Brega is a coastal industrial town in northeastern Libya known for its major oil refinery and petrochemical facilities on the Gulf of Sidra.
-
D.
Madayya
Madayya was a poet who served in the royal court of the Vijayanagara emperor Sri Krishnadevaraya.
-
E.
Safita
Safita is a historic hilltop town in western Syria known for its prominent Crusader-era fortress, the White Tower.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9e14b88190a2cee8e0c9bf31c8 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c10bb13481909650432d5c1f5872 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:49 p.m.