Triple
T37957762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rockford Forest Citys |
E946912
|
entity |
| Predicate | featuredEarlyCareerOf |
P136890
|
FINISHED |
| Object | Cap Anson |
E280429
|
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: Cap Anson | Statement: [Rockford Forest Citys, featuredEarlyCareerOf, Cap Anson]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredEarlyCareerOf Context triple: [Rockford Forest Citys, featuredEarlyCareerOf, Cap Anson]
-
A.
earlyCareerAt
Indicates that an entity spent the early part of its career working at or being affiliated with another entity.
-
B.
earlyCareerActivity
Indicates activities, roles, or engagements undertaken by an entity during the early stage of its career or professional development.
-
C.
employsEarlyInCareerOf
Indicates that one entity serves as an employer of another entity during the early stage of that other entity’s career.
-
D.
hasNotableEarlyCareerAppearanceOf
chosen
Indicates that an entity features or includes a significant appearance by another entity during the latter’s early career.
-
E.
coachedEarlyCareerOf
Indicates that one entity served as a coach or mentor to another during the early stage of that other entity’s career.
- 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_69f76ef64cf08190ad3e1114b62aac67 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41542a46348190948908471e652a9d |
completed | June 28, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.