Triple
T11794253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persaeus of Citium |
E280464
|
entity |
| Predicate | bornIn |
P1
|
FINISHED |
| Object | Citium |
E274030
|
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: Citium | Statement: [Persaeus of Citium, bornIn, Citium]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Citium Context triple: [Persaeus of Citium, bornIn, Citium]
-
A.
Citium
chosen
Citium was an ancient city on the southern coast of Cyprus, historically significant as a Phoenician-Greek trading center and the birthplace of the Stoic philosopher Zeno.
-
B.
Enasa
Enasa was a Spanish state-owned automotive manufacturer best known for producing Pegaso commercial vehicles and trucks.
-
C.
Quatis
Quatis is a small municipality in the state of Rio de Janeiro, Brazil, known for its location in the Sul Fluminense region and its predominantly rural character.
-
D.
Sempron
Sempron is a budget-oriented line of x86 processors from AMD designed for entry-level desktop and mobile computing.
-
E.
Poros
Poros is a river in J.R.R. Tolkien's Middle-earth that flows through Gondor and serves as a significant southern boundary.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a082d08190a42541396a06ed98 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f09115c66c8190b0a3e775bdf575c1 |
completed | April 28, 2026, 10:51 a.m. |
Created at: April 8, 2026, 9:42 p.m.