Triple
T37691414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Be the One: Six True Stories of Teens Overcoming Hardship with Hope |
E938513
|
entity |
| Predicate | numberOfProfiles |
P204343
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Be the One: Six True Stories of Teens Overcoming Hardship with Hope, numberOfProfiles, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfProfiles Context triple: [Be the One: Six True Stories of Teens Overcoming Hardship with Hope, numberOfProfiles, 6]
-
A.
numberOfPositions
Indicates the total count of distinct positions or roles associated with a given entity.
-
B.
numberOfNames
Indicates the count of distinct names associated with a given entity.
-
C.
numberOfModels
Indicates the quantity or count of models associated with a given entity or context.
-
D.
numberOfGroup
Indicates the total count of groups associated with or contained by a given entity.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69f76ed881408190bc62a969530a4a53 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:18 p.m.