Triple
T2858980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caria |
E63271
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Euromos
Euromos was an ancient Greek city in the region of Caria in southwestern Asia Minor, noted especially for its well-preserved Temple of Zeus.
|
E306435
|
NE FINISHED |
How this triple was built (4 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: Euromos | Statement: [Caria, hasMajorCity, Euromos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Euromos Context triple: [Caria, hasMajorCity, Euromos]
-
A.
Europaeum
Europaeum is a network of leading European universities dedicated to promoting academic collaboration, European studies, and cross-border dialogue in higher education.
-
B.
UNA Europa
UNA Europa is a European university alliance that brings together leading research-intensive universities to foster transnational collaboration in education, research, and innovation.
-
C.
Rada
Rada is the commonly used short name for Ukraine’s unicameral national parliament, the Verkhovna Rada.
-
D.
Europol
Europol is the European Union’s law enforcement agency that supports member states in combating serious international crime and terrorism.
-
E.
EUG
EUG is the IATA airport code for Mahlon Sweet Field, the primary commercial airport serving Eugene and the surrounding region in western Oregon, United States.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Euromos Triple: [Caria, hasMajorCity, Euromos]
Generated description
Euromos was an ancient Greek city in the region of Caria in southwestern Asia Minor, noted especially for its well-preserved Temple of Zeus.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Euromos Target entity description: Euromos was an ancient Greek city in the region of Caria in southwestern Asia Minor, noted especially for its well-preserved Temple of Zeus.
-
A.
Europaeum
Europaeum is a network of leading European universities dedicated to promoting academic collaboration, European studies, and cross-border dialogue in higher education.
-
B.
UNA Europa
UNA Europa is a European university alliance that brings together leading research-intensive universities to foster transnational collaboration in education, research, and innovation.
-
C.
Rada
Rada is the commonly used short name for Ukraine’s unicameral national parliament, the Verkhovna Rada.
-
D.
Europol
Europol is the European Union’s law enforcement agency that supports member states in combating serious international crime and terrorism.
-
E.
EUG
EUG is the IATA airport code for Mahlon Sweet Field, the primary commercial airport serving Eugene and the surrounding region in western Oregon, United States.
- F. None of above. chosen
Provenance (5 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf8aec3c8190a4168d8c916b5268 |
completed | March 7, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d972aa481908f6cb5f27706990c |
completed | March 10, 2026, 1:33 p.m. |
| NEDg | Description generation | batch_69b021fbc2808190b415fd8af934cf73 |
completed | March 10, 2026, 1:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b02656f8488190ab0d715d1634b6a7 |
completed | March 10, 2026, 2:10 p.m. |
Created at: March 6, 2026, 10:02 p.m.