Triple
T37025037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gun Violence Memorial Project |
E916330
|
entity |
| Predicate | isTraveling |
P186920
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Gun Violence Memorial Project, isTraveling, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTraveling Context triple: [Gun Violence Memorial Project, isTraveling, true]
-
A.
offersInternationalTravel
Indicates that an entity provides or makes available travel services or opportunities that involve crossing national borders.
-
B.
requiresPreparationForTravel
Indicates that one entity must undergo or arrange certain preparations before it can travel to or be transported to another entity or location.
-
C.
oftenTravelsWith
Indicates that one entity frequently accompanies another entity when traveling or moving between places.
-
D.
hasNotableTraveler
Indicates that an entity is associated with a traveler who is considered notable or significant in some recognized way.
-
E.
travelsFor
Indicates that one entity moves from place to place on behalf of, or for the benefit or purpose of, another entity or objective.
- 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_69f76e92c7648190bcfa277f64c71a21 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fb154b5f8c819089103b41f51a1639 |
completed | May 6, 2026, 10:17 a.m. |
Created at: May 3, 2026, 4:14 p.m.