Triple
T5848784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wellington County, Ontario |
E129776
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Erin |
E286018
|
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: Erin | Statement: [Wellington County, Ontario, containsMunicipality, Erin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erin Context triple: [Wellington County, Ontario, containsMunicipality, Erin]
-
A.
Erin
Erin Jobs is the daughter of Apple co-founder Steve Jobs and his wife Laurene Powell Jobs.
-
B.
Erin
chosen
Erin is a feminine given name commonly used in English-speaking countries, often associated with the poetic name for Ireland.
-
C.
Clare
Clare is a historic market town and civil parish in Suffolk, England, known for its medieval architecture and picturesque countryside setting.
-
D.
Clare
Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
-
E.
Clare
Clare is a small town in South Australia that serves as the main service and tourism hub for the surrounding Clare Valley wine region.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c035145a0c8190941945a83a3f2416 |
completed | March 22, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1b052288190ace51e65f1d888ab |
completed | March 23, 2026, 2:13 a.m. |
Created at: March 22, 2026, 3:55 p.m.