Triple
T610203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvard Law School Library |
E12080
|
entity |
| Predicate | collectionScope |
P17067
|
FINISHED |
| Object | United States law |
—
|
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: United States law | Statement: [Harvard Law School Library, collectionScope, United States law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectionScope Context triple: [Harvard Law School Library, collectionScope, United States law]
-
A.
collectsFrom
Indicates that one entity gathers, receives, or takes something (such as items, data, or payments) from another entity.
-
B.
collectionSize
Indicates the total number of items contained within a specified collection.
-
C.
coveredGroup
Indicates that one group or set is included within, or has its members protected or accounted for by, another group or arrangement.
-
D.
collectingArea
Indicates the total surface area over which something (typically a device or system) gathers or receives a substance, signal, or resource.
-
E.
collectorStatus
Indicates the current operational or lifecycle state of a collector in relation to its collection activity.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df68f2c8190a0ee9da4692b2a62 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cfa7b4481909bec7a5fd3e98c65 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.