Triple
T79332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Hall |
E1591
|
entity |
| Predicate | residents |
P2750
|
FINISHED |
| Object | Harvard College freshmen |
—
|
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: Harvard College freshmen | Statement: [Lionel Hall, residents, Harvard College freshmen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residents Context triple: [Lionel Hall, residents, Harvard College freshmen]
-
A.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
B.
hasNotableResident
Indicates that an entity is or has been a well-known or distinguished resident of a particular place or location.
-
C.
populationIncludes
chosen
Indicates that a population contains or encompasses the specified individual(s) or subgroup(s) as members or elements.
-
D.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
E.
district
Indicates that one entity is an administrative or electoral district that geographically contains or governs another entity.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eb126b48190b410b859c1be99aa |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.