Triple
T7732590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quincy, Massachusetts |
E175296
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object | Wollaston |
E8410
|
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: Wollaston | Statement: [Quincy, Massachusetts, hasNeighborhood, Wollaston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wollaston Context triple: [Quincy, Massachusetts, hasNeighborhood, Wollaston]
-
A.
Wollaston
Wollaston is an English surname most notably associated with William Hyde Wollaston, the chemist and physicist who discovered the elements palladium and rhodium.
-
B.
Wollaston
chosen
Wollaston is a Massachusetts Bay Transportation Authority (MBTA) rapid transit station on the Red Line located in Quincy, Massachusetts.
-
C.
Lapworth
Lapworth is an English surname most notably associated with Charles Lapworth, a pioneering geologist known for his work on Ordovician stratigraphy.
-
D.
Moseley
Moseley is a surname most notably associated with Jonny Moseley, the American Olympic gold medal–winning freestyle skier.
-
E.
Daubeny
Daubeny is an English surname derived from the Norman French family name d’Aubigny.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7033863d881909451a4f9675021a3 |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b531a7f481908e4ff7f15b851070 |
completed | March 29, 2026, 5:14 a.m. |
Created at: March 27, 2026, 4:06 p.m.