Triple
T1705811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argive plain |
E36869
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Argolis |
E131460
|
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: Argolis | Statement: [Argive plain, locatedIn, Argolis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Argolis Context triple: [Argive plain, locatedIn, Argolis]
-
A.
Argolis
chosen
Argolis is a historic region in the northeastern Peloponnese of Greece, known for its rich archaeological heritage and ancient city-states.
-
B.
Cloyce
Cloyce is a surname most notably associated with Sarah Cloyce, one of the women accused during the Salem witch trials in 17th-century Massachusetts.
-
C.
Quarles
Quarles is a surname of English origin borne by various notable individuals, including politicians, judges, and writers.
-
D.
Lohse
Lohse is a German surname borne by various notable individuals in fields such as science, sports, and the arts.
-
E.
Aldridge
Aldridge is an English-origin surname borne by various notable individuals in fields such as sports, entertainment, and the arts.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62f52ea48190a176eb499f946301 |
completed | March 6, 2026, 5:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ad3b9c481909f83f7045789e49d |
completed | March 8, 2026, 2:42 p.m. |
Created at: March 4, 2026, 7:30 p.m.