Triple
T4143111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amanda Reed |
E89318
|
entity |
| Predicate | visionLedTo |
P18658
|
FINISHED |
| Object | establishment of Reed College |
—
|
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: establishment of Reed College | Statement: [Amanda Reed, visionLedTo, establishment of Reed College]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visionLedTo Context triple: [Amanda Reed, visionLedTo, establishment of Reed College]
-
A.
visionOf
Indicates that one entity is a visual representation, image, or depiction of another entity.
-
B.
canLeadTo
chosen
Indicates that one entity, condition, or event has the potential to cause, result in, or bring about another.
-
C.
hasVisionOf
Indicates that one entity perceives, imagines, or foresees another entity or scenario, typically in a mental, prophetic, or visualized form.
-
D.
containsVisionOf
Indicates that one entity includes, depicts, or embodies a visual representation or image of another entity.
-
E.
missionLed
Indicates that an entity served as the leader or commander of a particular mission.
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.