Triple
T202927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irin Carmon |
E4544
|
entity |
| Predicate | coveredTopic |
P450
|
FINISHED |
| Object | reproductive justice |
—
|
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: reproductive justice | Statement: [Irin Carmon, coveredTopic, reproductive justice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coveredTopic Context triple: [Irin Carmon, coveredTopic, reproductive justice]
-
A.
covered
Indicates that one entity lies over or on top of another entity so as to conceal, protect, or obscure it.
-
B.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
C.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
D.
explored
Indicates that an entity has traveled through, examined, or investigated another entity or area, typically to discover or learn more about it.
-
E.
explores
Indicates actively investigating, traveling through, or examining something in order to discover or learn more about it.
- F. None of above.
Provenance (3 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25f46b4f081909e5ee3718109a71f |
completed | Feb. 28, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69a25b4b42ec8190bef16bbbdd30a742 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.