Triple
T16372839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horse Mounted Unit |
E397606
|
entity |
| Predicate | patrolMethod |
P123146
|
FINISHED |
| Object | horseback |
—
|
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: horseback | Statement: [Horse Mounted Unit, patrolMethod, horseback]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: patrolMethod Context triple: [Horse Mounted Unit, patrolMethod, horseback]
-
A.
patrolType
Indicates the specific kind or category of patrol activity being carried out or assigned.
-
B.
patrolledBy
Indicates that an area, route, or domain is regularly monitored or guarded by a specific agent or group.
-
C.
policePresence
Indicates that law enforcement officers are present at or monitoring a particular location, event, or situation.
-
D.
patroonOf
Indicates a relationship in which one entity acts as a patron, sponsor, or protector providing support or resources to another entity.
-
E.
policeUnit
Indicates that one entity is a police unit (such as a department, squad, or division) associated with or responsible for 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff4327248190a7c6bf01a81fd9b4 |
completed | April 18, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:08 a.m.