Triple
T4537741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodland, California |
E107447
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Woodland |
E107447
|
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: Woodland | Statement: [Woodland, California, hasName, Woodland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woodland Context triple: [Woodland, California, hasName, Woodland]
-
A.
Woodland
chosen
Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
-
B.
Woodland
Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
-
C.
Woodlands
Woodlands is a residential neighbourhood located within the city of Pickering in Ontario, Canada.
-
D.
Woodlands
Woodlands is a residential and commercial town in northern Singapore that serves as a key land border crossing point to Malaysia across the Straits of Johor.
-
E.
Woodlands
Woodlands is a natural, forested area within Belle Isle Park that offers visitors scenic trails and a tranquil escape into nature.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b8c4788190b35d110553013ff1 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacfb2ba48190b7f1b23785e9d030 |
completed | March 20, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:04 p.m.