Triple
T10518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Residence Act |
E214
|
entity |
| Predicate | maximumSize |
P99
|
FINISHED |
| Object | 100 square miles |
—
|
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: 100 square miles | Statement: [Residence Act, maximumSize, 100 square miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumSize Context triple: [Residence Act, maximumSize, 100 square miles]
-
A.
collectionSize
Indicates the total number of items contained within a specified collection.
-
B.
hasLimitation
chosen
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
C.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
D.
length
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
E.
medium
Indicates that an entity serves as the means, channel, or intermediary through which an action, communication, or effect is carried out between other entities.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242cd8fb481909562f114f4ce7700 |
completed | Feb. 28, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69a23fe6b0bc8190bcce9b74f2c5fb08 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.