Triple
T37539196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sethekk Halls |
E933282
|
entity |
| Predicate | featuresEncounter |
P111040
|
FINISHED |
| Object | Anzu |
E765160
|
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: Anzu | Statement: [Sethekk Halls, featuresEncounter, Anzu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresEncounter Context triple: [Sethekk Halls, featuresEncounter, Anzu]
-
A.
settingEncounter
Indicates that an encounter or interaction is taking place within a particular setting or environment.
-
B.
featuresDisease
Indicates that an entity exhibits, presents, or is characterized by a particular disease.
-
C.
encounterStyle
Indicates the manner or format in which two or more entities meet, interact, or come into contact with each other.
-
D.
featuresSituation
chosen
Indicates that a situation is characterized by, or has as one of its defining aspects, the specified feature or element.
-
E.
encounterStructure
Indicates a relationship where an entity comes into contact with or experiences a particular structure or constructed arrangement.
- F. None of above.
Provenance (4 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a409f06178c8190b8bf413af4e2fa46 |
completed | June 28, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.