Triple
T353405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spruce Street (Philadelphia) |
E7490
|
entity |
| Predicate | hasAdjacentUse |
P12165
|
FINISHED |
| Object | university buildings |
—
|
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: university buildings | Statement: [Spruce Street (Philadelphia), hasAdjacentUse, university buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentUse Context triple: [Spruce Street (Philadelphia), hasAdjacentUse, university buildings]
-
A.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
B.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
C.
usedBefore
Indicates that one entity was utilized or applied prior to the use or occurrence of another entity.
-
D.
laterUsedBy
Indicates that something is subsequently utilized or employed by a specified entity at a later time.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- F. None of above. chosen
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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb80f524819093f4c2c18c3d615f |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e9571bd88190b6fcb16f21604720 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0a4c448190a8a179daa9b90645 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.