Triple
T3988217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Physics Teacher |
E86923
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | AAPT |
E86922
|
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: AAPT | Statement: [The Physics Teacher, associatedWith, AAPT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AAPT Context triple: [The Physics Teacher, associatedWith, AAPT]
-
A.
AAPT
chosen
AAPT is a professional organization dedicated to advancing the teaching and learning of physics at all educational levels.
-
B.
AAPT Executive Office
The AAPT Executive Office is the administrative body of the American Association of Physics Teachers responsible for managing and coordinating its major activities and events.
-
C.
Appar
Appar was a prominent 7th-century Tamil Shaivite saint and poet whose devotional hymns greatly shaped the Bhakti movement in South India.
-
D.
APG
APG is an internationally recognized collaborative group of botanists that develops and maintains a modern, phylogeny-based classification system for flowering plants.
-
E.
Apt
Apt is a historic market town in southeastern France’s Vaucluse department, known for its candied fruit production and Provençal charm.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9ff54708190be56f48569ce97a4 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c4d0f348190841fe13bff0fef00 |
completed | March 14, 2026, 11:53 a.m. |
Created at: March 9, 2026, 3:33 p.m.