Triple
T11720528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgetown Hoyas track and field |
E278616
|
entity |
| Predicate | recruitingFocus |
P100977
|
FINISHED |
| Object | middle-distance runners |
—
|
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: middle-distance runners | Statement: [Georgetown Hoyas track and field, recruitingFocus, middle-distance runners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recruitingFocus Context triple: [Georgetown Hoyas track and field, recruitingFocus, middle-distance runners]
-
A.
recruitingScope
Indicates the extent or boundaries within which recruiting activities are conducted or targeted.
-
B.
recruitmentBase
Indicates the foundational source, location, or context from which recruitment efforts or recruited entities originate.
-
C.
recruitmentFrom
Indicates that one entity recruits or sources members, employees, or participants from another entity.
-
D.
employerFocus
Indicates that an employer directs particular attention, resources, or priority toward a specific subject, group, or area.
-
E.
recruitsFor
Indicates that one entity actively seeks out, enlists, or brings in participants, members, or resources on behalf of another entity, such as an organization, event, or cause.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4c26e4c8190ae30d906b4fd4221 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:40 p.m.