Triple
T20613911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Achan |
E506516
|
entity |
| Predicate | associatedWithPlace |
P2830
|
FINISHED |
| Object | Ai |
—
|
NE NERFINISHED |
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: Ai | Statement: [Achan, associatedWithPlace, Ai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ai Context triple: [Achan, associatedWithPlace, Ai]
-
A.
Ai
chosen
Ai is an ancient Canaanite city mentioned in the Hebrew Bible, particularly in the Book of Joshua, as a site of early Israelite military campaigns.
-
B.
Ai
Ai is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into broader Chinese society.
-
C.
AI
Amnesty International is a global non-governmental organization focused on protecting human rights and campaigning against abuses such as torture, unjust imprisonment, and the death penalty.
-
D.
AI
Allen Iverson is a Hall of Fame former NBA point guard and shooting guard renowned for his scoring ability, quickness, and cultural impact on basketball.
-
E.
AI
AI (Artificial Intelligence) is a field of computer science focused on creating systems that can perform tasks typically requiring human intelligence, such as learning, reasoning, and problem-solving.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aada19e481909363428ceda67603 |
completed | April 20, 2026, 10:38 p.m. |
Created at: April 16, 2026, 11:41 a.m.