Triple
T23351485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucia of Tripoli |
E592922
|
entity |
| Predicate | titleHolderOf |
P38
|
FINISHED |
| Object | Tripoli |
—
|
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: Tripoli | Statement: [Lucia of Tripoli, titleHolderOf, Tripoli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tripoli Context triple: [Lucia of Tripoli, titleHolderOf, Tripoli]
-
A.
Tripoli
Tripoli was a 12th-century nobleman, the son of Bohemond III of Antioch, associated with the Crusader states in the Levant.
-
B.
Tripoli
Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
-
C.
Tripoli
chosen
Tripoli is Lebanon’s second-largest city, a historic Mediterranean port known for its medieval Mamluk architecture and vibrant commercial life.
-
D.
Tripoli
Tripoli is a historic city in the central Peloponnese of Greece that serves as the main urban and administrative center of the Arcadia region.
-
E.
Tripoli
Tripoli was a historic American shipyard and port city involved in constructing naval vessels such as the USS Intrepid.
- 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a1401748190b77df0a45c2aeebf |
completed | April 29, 2026, 5:41 a.m. |
Created at: April 17, 2026, 5:20 p.m.