Triple
T17573534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Land USA |
E427998
|
entity |
| Predicate | crossReconstruction |
P128069
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Holy Land USA, crossReconstruction, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossReconstruction Context triple: [Holy Land USA, crossReconstruction, 2013]
-
A.
crossStructure
Indicates that one entity passes over, through, or across the physical span or boundary defined by another structure.
-
B.
crossWith
Indicates that one entity intersects or passes over/through the path, boundary, or position of another entity.
-
C.
crossCut
Indicates that one entity intersects or passes through another, typically cutting across it from one side to the other.
-
D.
crossReference
Indicates that one entity refers the user to another related entity or source for additional or supporting information.
-
E.
crossType
Indicates a relationship where one entity intersects, passes over, or traverses another, typically implying movement or extension across a boundary, area, or medium.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e459330c788190907a02fc98e0e24b |
completed | April 19, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb50b448190a59dd4be33c76db7 |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:50 a.m.