Triple
T10844323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of the Woodland Realm |
E255972
|
entity |
| Predicate | associatedWithRealm |
P48425
|
FINISHED |
| Object | Woodland Realm |
E255973
|
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 Realm | Statement: [Prince of the Woodland Realm, associatedWithRealm, Woodland Realm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woodland Realm Context triple: [Prince of the Woodland Realm, associatedWithRealm, Woodland Realm]
-
A.
Woodland Realm
chosen
The Woodland Realm is the Elven kingdom in northern Mirkwood ruled by Thranduil in J.R.R. Tolkien’s Middle-earth legendarium.
-
B.
Woodland
Woodland is a small city in California’s Sacramento Valley known as an agricultural and administrative hub for Yolo County.
-
C.
Woodland
Woodland is a small, affluent residential city located in Hennepin County, Minnesota, known for its wooded landscapes and lakeside properties.
-
D.
Woodland
Woodland is an episode of the British nature documentary series "Wild Isles" that explores the wildlife and ecosystems of the United Kingdom’s forests and woodlands.
-
E.
Woodland
Woodland is a small city located in Talbot County, Georgia, in the United States.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d750cf3fd08190b9c509929dc43284 |
completed | April 9, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7ca05788190aff4f34084499ba6 |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:19 p.m.