Triple
T14514812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTV |
E340488
|
entity |
| Predicate | volunteerLabel |
P114544
|
FINISHED |
| Object | included many regular Italian army personnel |
—
|
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: included many regular Italian army personnel | Statement: [CTV, volunteerLabel, included many regular Italian army personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volunteerLabel Context triple: [CTV, volunteerLabel, included many regular Italian army personnel]
-
A.
volunteeredFor
Indicates that an entity willingly offered their time or services to support or participate in an activity, cause, or organization.
-
B.
typeOfVolunteerUnit
Indicates that one entity is a specific kind or category of volunteer unit in relation to another entity.
-
C.
hasVolunteerStatus
Indicates that an entity holds a particular volunteer-related status or role within a specified context.
-
D.
volunteerRequirement
Indicates that an entity has a condition or obligation specifying the need for volunteers or volunteer participation.
-
E.
hasVolunteerProgram
Indicates that an organization or entity offers an organized program through which individuals can volunteer their time or services.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a6d82988190b6f957012bcc63d4 |
completed | April 14, 2026, 7:50 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:21 a.m.