Triple
T25116971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Hardiman |
E629154
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Histories for the Subordinated
Histories for the Subordinated is a historical study by David Hardiman that examines the experiences, agency, and perspectives of marginalized and oppressed groups often overlooked in mainstream historiography.
|
E1660864
|
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: Histories for the Subordinated | Statement: [David Hardiman, notableWork, Histories for the Subordinated]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Histories for the Subordinated Triple: [David Hardiman, notableWork, Histories for the Subordinated]
Generated description
Histories for the Subordinated is a historical study by David Hardiman that examines the experiences, agency, and perspectives of marginalized and oppressed groups often overlooked in mainstream historiography.
Provenance (5 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_69e2ff3169d08190973b6061d5009abd |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f465c7b88c81909fefbf647d1b810d |
completed | May 1, 2026, 8:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1048f93d548190b6dba081fbf8a913 |
completed | May 22, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_6a1049d7d4bc819081cf52476b0c0a1d |
completed | May 22, 2026, 12:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a104a50e59c81908e576aeb2cebc1c5 |
completed | May 22, 2026, 12:21 p.m. |
Created at: April 18, 2026, 6:27 a.m.