Triple
T11558691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hippodamia |
E274077
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Dias |
E558915
|
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: Dias | Statement: [Hippodamia, child, Dias]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dias Context triple: [Hippodamia, child, Dias]
-
A.
Dias
chosen
Dias is a Portuguese-language surname shared by numerous individuals, including notable figures in arts, sports, and public life.
-
B.
Dina
Dina is a town in Pakistan’s Punjab province, located within the Jhelum District and known as a local commercial and transport hub.
-
C.
Dina
Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
-
D.
Paiva
Paiva is a wine-producing subregion within Portugal’s Vinho Verde appellation, known for its fresh, light-bodied white wines.
-
E.
Diez
Diez is a small historic town in western Germany’s Rhineland-Palatinate, known for its picturesque setting on the Lahn River and its prominent hilltop castle.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a888e8481909386009b9603e4d3 |
completed | April 10, 2026, 5:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e87953088190b72d0afeb9251535 |
completed | April 21, 2026, 3:01 a.m. |
Created at: April 8, 2026, 9:37 p.m.