Triple
T9335177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hippolytus |
E224624
|
entity |
| Predicate | settingLocation |
P40
|
FINISHED |
| Object | Troezen |
E70938
|
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: Troezen | Statement: [Hippolytus, settingLocation, Troezen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Troezen Context triple: [Hippolytus, settingLocation, Troezen]
-
A.
Troezen
chosen
Troezen is an ancient Greek city in the northeastern Peloponnese, historically significant as a political and cultural center and as the legendary birthplace of the hero Theseus.
-
B.
Troost
Troost is a German surname most notably associated with Paul Troost, an influential early 20th-century architect.
-
C.
Trost
Trost is a surname most notably associated with Barry M. Trost, an influential American chemist known for his work in organic synthesis and the concept of atom economy.
-
D.
Tullistes
Tullistes are the inhabitants of the French city of Tulle, located in the Corrèze department in central France.
-
E.
Marié
Marié is a given name variant of Marie, commonly used in French and other Romance-language contexts.
- 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_69ca84286fcc81909f6e7fd7a7e862a2 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37f031888190a90d263d225d163c |
completed | April 1, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e3ce039081909c1f6fe0c52d6b54 |
completed | April 4, 2026, 10:11 a.m. |
Created at: March 30, 2026, 7:39 p.m.