Triple
T5547399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Ellen Trainor |
E145441
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Trainor |
E501249
|
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: Trainor | Statement: [Mary Ellen Trainor, familyName, Trainor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trainor Context triple: [Mary Ellen Trainor, familyName, Trainor]
-
A.
Trainor
chosen
Trainor is the surname of American pop singer-songwriter Meghan Trainor, known for hits like "All About That Bass."
-
B.
Trainer
Trainer is a TensorFlow Extended component responsible for training machine learning models within end-to-end ML pipelines.
-
C.
Trotter
Trotter is the surname of Tariq "Black Thought" Trotter, the acclaimed rapper, lead MC of The Roots, and influential figure in hip-hop.
-
D.
Treveris
Treveris is the historical city now known as Trier, one of the oldest cities in Germany and a major center of the Roman Empire in the region.
-
E.
Troulos
Troulos is a small coastal village and popular beach resort on the Greek island of Skiathos in the Sporades.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe0244c8190aeb995f79f22a039 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0282ace308190a714685579f2a789 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:35 p.m.