Triple
T918671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urban Jungle |
E19829
|
entity |
| Predicate | primaryExperience |
P22360
|
FINISHED |
| Object | up-close encounters with large mammals |
—
|
LITERAL 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: up-close encounters with large mammals | Statement: [Urban Jungle, primaryExperience, up-close encounters with large mammals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryExperience Context triple: [Urban Jungle, primaryExperience, up-close encounters with large mammals]
-
A.
experiences
Indicates that an entity undergoes, feels, or is affected by a particular event, state, or condition.
-
B.
primaryPosition
Indicates the main role, job, or position an entity holds among potentially multiple positions.
-
C.
softwareExperience
Indicates the level or extent of a person's prior experience working with or using specific software.
-
D.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
-
E.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
- F. None of above. chosen
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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2944ff88190a260be5355132ba5 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b385176081909e3e8c3f647c1fd4 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.