Triple
T157388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triumphal Entry into Jerusalem |
E3208
|
entity |
| Predicate | featuresCrowdAction |
P81
|
FINISHED |
| Object | crowds spread cloaks on the road |
—
|
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: crowds spread cloaks on the road | Statement: [Triumphal Entry into Jerusalem, featuresCrowdAction, crowds spread cloaks on the road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCrowdAction Context triple: [Triumphal Entry into Jerusalem, featuresCrowdAction, crowds spread cloaks on the road]
-
A.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
B.
activity
chosen
Indicates that an entity is engaged in or performing a particular action, behavior, or process.
-
C.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
D.
movementIn
Indicates a relationship where an entity moves within, into, or inside a specified area, space, or container.
-
E.
eventRole
Indicates the specific function, capacity, or part an entity plays within an event or occurrence.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25830136881909f5ecb2cb22097b2 |
completed | Feb. 28, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69a2565f30848190a2a71fdb7dc140b5 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.