Triple
T4536403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Macedonia |
E107418
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Serres |
E104307
|
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: Serres | Statement: [Central Macedonia, containsCity, Serres]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serres Context triple: [Central Macedonia, containsCity, Serres]
-
A.
Serres
chosen
Serres is a historic city in northern Greece known for its Byzantine heritage and role as a regional economic and cultural center.
-
B.
San Javier
San Javier is a Chilean town known for its agricultural activity and wine production in the Maule Region.
-
C.
San Javier
San Javier is a municipality in Spain’s Region of Murcia, known for hosting the Spanish Air and Space Force’s main officer training academy and its nearby coastal and lagoon areas on the Mar Menor.
-
D.
Lavezares
Lavezares is a coastal municipality in the province of Northern Samar in the Philippines, known for its fishing communities and island landscapes.
-
E.
San Fernando
San Fernando is a major industrial and commercial city located in the southern part of Trinidad, known for its energy sector and bustling urban center.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdb9193e2481908901b9b4eb307da8 |
completed | March 20, 2026, 9:16 p.m. |
Created at: March 20, 2026, 1:04 p.m.