Triple
T4416712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Programs with Common Sense |
E94991
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | AI planning |
E267834
|
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: AI planning | Statement: [Programs with Common Sense, influenced, AI planning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AI planning Context triple: [Programs with Common Sense, influenced, AI planning]
-
A.
Intelligent Systems
Intelligent Systems is a Japanese video game development company best known for creating the Fire Emblem and Paper Mario series.
-
B.
.ai
.ai is the country code top-level domain (ccTLD) associated with Anguilla that has become popular worldwide for artificial intelligence-related websites.
-
C.
Ai
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.
-
D.
Ai
Ai is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into broader Chinese society.
-
E.
General Problem Solver
chosen
The General Problem Solver is an early artificial intelligence program designed to model and automate human-like problem-solving across a wide range of domains using general search and reasoning strategies.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551afb448190a2ce2000193808ac |
completed | March 13, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f61b56a8819099b5302f1b53f76d |
completed | March 14, 2026, 11:58 p.m. |
Created at: March 12, 2026, 11:29 p.m.