Triple
T34601239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergeant Morgan O’Rourke |
E888463
|
entity |
| Predicate | originalMediumCountry |
P154974
|
FINISHED |
| Object | United States |
E14
|
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: United States | Statement: [Sergeant Morgan O’Rourke, originalMediumCountry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalMediumCountry Context triple: [Sergeant Morgan O’Rourke, originalMediumCountry, United States]
-
A.
mediumOfOriginCountry
chosen
Indicates that the medium (e.g., artwork, recording, or material) originates from or is associated with a specified country.
-
B.
mediumOfOrigin
Indicates the original physical or digital medium from which an item, work, or data was derived or obtained.
-
C.
originallyProducedIn
Indicates that something was first created, manufactured, or brought into existence in a particular place or location.
-
D.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
E.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
- 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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3740f3f4e48190b2231afb605cffc7 |
completed | June 21, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:03 a.m.