Triple
T19220857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panya Clark Espinal |
E480607
|
entity |
| Predicate | influencesOrThemes |
P87217
|
FINISHED |
| Object | urban experience |
—
|
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: urban experience | Statement: [Panya Clark Espinal, influencesOrThemes, urban experience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesOrThemes Context triple: [Panya Clark Espinal, influencesOrThemes, urban experience]
-
A.
influencesFocus
Indicates that one entity affects or shapes the attention, concentration, or focal priorities of another entity.
-
B.
movementInfluences
Indicates that one entity’s movement affects, alters, or determines the movement or motion-related behavior of another entity.
-
C.
wereInfluencedBy
chosen
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
D.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
E.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
- F. None of above.
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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa3e8d488190a93fb743dabd0ffb |
completed | April 20, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69e4dcf22b3c8190bee02e3af946e114 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:24 p.m.