Triple

T37753413

Position	Surface form	Disambiguated ID	Type / Status
Subject	Texas City disaster of 1947	`E941044`	entity
Predicate	startedOnVessel	`P203208`	FINISHED
Object	SS Grandcamp SS Grandcamp was a French cargo ship whose catastrophic explosion in Texas City, Texas, in 1947 caused one of the deadliest industrial disasters in U.S. history.	`E2242731`	NE FINISHED

How this triple was built (3 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: SS Grandcamp | Statement: [Texas City disaster of 1947, startedOnVessel, SS Grandcamp]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: SS Grandcamp
Triple: [Texas City disaster of 1947, startedOnVessel, SS Grandcamp]

Generated description

SS Grandcamp was a French cargo ship whose catastrophic explosion in Texas City, Texas, in 1947 caused one of the deadliest industrial disasters in U.S. history.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: startedOnVessel
Context triple: [Texas City disaster of 1947, startedOnVessel, SS Grandcamp]

A. aboardShip
Indicates that one entity is physically on or inside a ship, typically as a passenger, crew member, or cargo.
B. hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
C. vesselLaunched
Indicates that a vessel has been formally set afloat or put into operation at a specific time or place.
D. shipBoardedFrom
Indicates that an entity boarded a ship originating from or at a specified location or source.
E. isVesselFor
Indicates that one entity functions as a container or medium specifically used to hold, carry, or convey another entity.
F. None of above. chosen

Provenance (7 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_69f76ee1f3a88190834e6c8af99bccc9`	completed	May 3, 2026, 3:50 p.m.
NER	Named-entity recognition	`batch_6a013b78bde881909a082beced4e0157`	completed	May 11, 2026, 2:14 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a40e07b9bf481909787fcc0f2dc7dee`	completed	June 28, 2026, 8:51 a.m.
NEDg	Description generation	`batch_6a40e0eb9f5881909b459d91abf800d5`	completed	June 28, 2026, 8:52 a.m.
NED2	Entity disambiguation (via description)	`batch_6a40ea896840819082dd572e2e9e882a`	completed	June 28, 2026, 9:34 a.m.
PD	Predicate disambiguation	`batch_6a013acf45508190a999b208066072bd`	completed	May 11, 2026, 2:11 a.m.
PDg	Predicate description generation	`batch_6a013b7808f08190979d68007e1882c6`	completed	May 11, 2026, 2:14 a.m.

Created at: May 3, 2026, 4:19 p.m.